critical regions in Hypothesis Testing

Practice Problems on Hypothesis Testing

Hypothesis testing helps us to validate the various claims made by different people in different scenario. For example if we claim that there is no significant difference between boys and girls intelligence level. So can we validate it significantly? Or can we validate that smoking causes cancer?

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Homogeneous Data Nodes

A Complete Guide to Decision Tree Formation and Interpretation in Machine Learning

Decision Tree is supervised machine learning algorithm which is used for both types of problems regression (that is predicting the continuous value for future example house price, hours the match can be played given overcast condition etc…) and classification (that is classifying different objects into respective categories or classes for example given the overcast conditions match will be played or not, given image belongs to cat or dog etc…).

Which industries will benefit most from Artificial Intelligence and Machine Learning in 2022

Artificial intelligence and machine learning are two of the hottest topics of discussion in recent times. We get to hear these terms very commonly due to their wide array of applications in different types of industries. Both these technologies are evolving at a great pace. Most importantly, a blend of the two makes it even more powerful. It is precisely the reason why the current trend lies in focusing on an appropriate combination of AI and ML to enhance its potential further. And this makes industries to gain more profits.

Precision-Recall vs ROC-AUC curve

What is the difference between Precision-Recall Curve vs ROC-AUC curve?

In Machine Learning, it is very important to have good understanding of different performance metrics. And it is even more important to know when to use which one to correctly explain the model performance. In classification problems more specific to binary classification, you can not conclude your model without plotting Precision-Recall curve and ROC-AUC curve. In this post, will learn what is the main difference between Precision-Recall curve and ROC-AUC curve and when to use which one.

Decision Tree for Regression

Decision Tree for Regression Models in Machine Learning

The ID3 algorithm can be used to construct a decision tree for regression type problems by replacing Information Gain with Standard Deviation Reduction – SDR
A decision tree is built top down from a root node and involves partitioning the data into subsets that contain instances with similar values mean homogeneous data.
Here, standard deviation is used to calculate the homogeneity of a numerical sample (target variable).

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